This is the blog of David M. Raab, marketing technology consultant and analyst. Mr. Raab is Principal at Raab Associates Inc. The blog is named for the Customer Experience Matrix, a tool to visualize marketing and operational interactions between a company and its customers.

Friday, December 06, 2013

As I wrote last week, it sometimes seems that every system I look at these days is a Customer Data Platform. Of course, this is partly because I’m choosing to look at that type of system, and partly because CDP vendors are reaching out to me. But I do believe another reason is that CDPs are an idea whose time has come: I’ve recently seen at least three CDPs that are just emerging from stealth or beta mode. All were developed because someone else recognized the huge unmet need for getting better customer data to marketers.

One of the vendors that contacted me was Optimove, a Tel Aviv-based firm that calls itself a “retention automation platform” but definitely fits the CDP criteria. This means that Optimove is a marketer-controlled system that loads data from multiple source systems, puts it in a marketing-friendly format, and makes it available to external marketing execution systems.

Like many CPDs, Optimove also includes a campaign engine that pushes specific marketing actions to the external systems. Optimove’s approach is unusual in basing its campaign interface on a calendar that lays out the campaign schedule for each user-defined customer segment. This makes it easier for marketers to build a comprehensive contact strategy from multiple campaigns.

The campaigns themselves each have their own schedule, allowing them to run once, daily, weekly, or monthly. Users can also limit the number of messages sent to each customer by assigning an exclusion period to each campaign. Other campaigns can be instructed to respect or ignore these exclusion periods, ensuring that high priority messages are delivered in all circumstances. Each campaign triggers a single action, which can be directed to email, banner ads, direct mail, Facebook custom audiences, in-app pop-ups, SMS, app message boards, call centers, or other channels. The connections may be through file transfers or APIs.

Optimove's campaign interface is unusual, but the system is even more unusual in taking performance measurement very seriously. Its standard campaign setup requires users to assign a success measure and to either set aside a control group or set up a multi-way split of alternative treatments. This enables standard reports, including the campaign calendar itself, to show the incremental value provided by each campaign – the critical information needed for long-term optimization. By contrast, most marketing systems make success targets and testing optional if they support them at all. Users can also see a history of all campaign results for a given segment, making it even easier to identify the most productive programs.

The campaign segments themselves, which Optimove calls target groups, are built by accessing data that Optimove has loaded from the client’s data warehouse and operational systems. Optimove has standard data models for different industries, reflecting its current customer base: online gaming (bingo, casinos, poker, sports betting, etc.), foreign exchange trading, and ecommerce. The system assumes the data has already been coded with customer IDs, which something that makes reasonable sense given the focus on retention rather than acquisition.

Data is typically loaded daily or weekly. After each load, customers are assigned to life stages (typically, new customers, active customers, and churned customers) and to multiple segments based on behaviors and attributes, such as location, product preferences, and spending levels. The system then uses the life stages and segment attributes to assign customers to "microsegments" that cluster analysis has found will behave similarly. It’s important to understand microsegments represent a current customer state that will change over time: that is, each customer belongs to different microsegments at different stages in her life cycle.

Optimove calculates the probability of moving from one microsegment to the next and uses this to predict how a given group of customers will behave in the future. This is the basis for its lifetime value and churn predictions – key metrics in system reports. This type of forecasting is something else that really should be done by every marketing system, but rarely is. Optimove also provides cohort analysis reports, comparing performance of customers who joined during different time periods. This is yet another important type of information that is not always available.

Optimove does have some limitations. I was surprised there are no standard reports to highlight attributes that separate responders from non-responders within a promotion audience: this is pretty common information that helps marketers to refine their segmentations and better understand what is driving results. Nor does the system current recommend the best action to take with individual or a group. Both features are being worked on for future release.

Optimove was founded in 2009 and currently has about 70 clients, mostly in Europe. It has a few U.S. customers and is looking to expand in this market. Pricing is usually based on the number of customers and begins around $2,500 per month.